Idea Description
Supplementary Information
Innovation 'Elevator Pitch':
Giving one drop of blood for analysis by SOMAscan informs me of my current health status, and helps my doc give me the right advice to reverse or prevent further disease development, or guide their treatment recommendations that will work first time!
Overview of Innovation:
The measurement of 5,000 blood proteins (a quarter of the human protein repertoire) is now possible on a reproducible and industrial scale in clinically-accredited central lab settings. Prior analysis of hundreds of thousands of study subjects' and patient blood samples, whose basic & physiological measurements, life style and clinical histories have been collated, has been used to create a suite of health status defining algorithms that define risk of disease event occuring over 1-5 year time horizons, rates of development, and likelihood of response to alternative intervention that are available. Whereas rudimentary 'disease risk' insights such as Framingham cardiovascular diasease (CVD) risk scores and QRISK2 are used in public health, primary care and specialist acute care settings to augment disease prevention or guide optimal treatment choices, it is now possible to expand this range of probablistic medicine insights. Expanding the repertoire beyond CVD to include pre-diabetes conversion to full diabetes or development of complications (amputations, kidney failure, blindness) that lead to costly or catastrophic outcomes, is a starting point. However, diseases such as non-alcoholic fatty liver disease and steatohepatitis, which leads to liver cancer & failure is another silent killer whose development can be revealed just by applying a different status-prognosis algorithm to protein measurements derived from the same blood sample. Chronic disease management and care accounts for ~70% of healthcare costs with diabetes alone consuming 10% of the NHS' entire budget and so these are worthy of attention for prevention, early disease interception (at a reversible stage), or optimising existing care paths that maximise available resources to deliver disease management interventions. Our primary focus is to prolong and improve population wellbeing such that patient treatment outcomes leads to broad adoption. However, whereas traditional diagnoses rely heavily on clinical symptoms, SomaLogic's AI-derived algorithms consider the molecular underpinnings of disease. Clinically-defined diseases are treated in standardised ways which doesn't always work. Identifying patients with treatment-refractory disease could help target those into research programmes including clinical trials for novel regimens or pharmacological agents. A secondary output of routine adoption could be creation of an accelerated trial recruitment resource to attract pharma partners.
Stage of Development:
Evaluation stage - Representative model or prototype system developed and can be effectively evaluated
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Hi Tony,
Quick couple fo questions:
- you mentioned clinical trails that were taking place - have these started?
- also, you mentioned that currently the service is accesible on the device on which the service is used, but in the future this will move to a clound based service?  What steps do you have in place for Data protection and in meeting Information Governance requirements?

Kind regards
Could be anonymous.
1) Not yet.  The first UK Clinical Trial (with Leeds Primary Care physicians) will start early 2019 unless recruitment could start sooner. 
2) The wet-lab blood protein measurement takes place in Oxford.  Protein data that is generated by running SOMAscan analysis, and health parameters (if accessed, at all) derived from electronic health records are aggregated by SomaLogic in the US (cloud hosted).  The proteomic data processing is performed in the US, and the summary result (e.g. risk score or differential diagnsosis or prognosis) is then delivered back to the health system physician, to inform clinical decision-making, via an agreed mechanism, usually a pre-existing patient health portal.  Note that SomaLogic works with synonymised patient information; the health system partner de-anonymises the data.
At a company level, we are designing our systems, products, and contracts to be compliant with GDPR.  Data Protection training of the US employees was delivered a few months ago and we have plans to deliver training to our new UK employees.
If there are specific questions remaining then I'd be happy to direct these to my colleagues responsible for legal and compliance aspects of SomaLogic's business.

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